Mental Health Economics and Financing
DR. COLLENE LAWHORN: But we are very delighted to welcome today Dr. Dan Chisholm, a guest of the Global Mental Health team, to speak with us today. So today's talk is going to be structured in such that we will, of course, welcome and introduce you, but we've also asked our Director of the Center for Global Mental Health Research to help frame this talk to give us more insights into health economics and how we can begin to think about that at NIMH and across NIH.
So this talk is being sponsored by NIMH's Global Mental Health team which is an interdisciplinary cross-cutting team made up of folks across the institute who work in partnership with the Center for Global Mental Health Research aimed at achieving global mental health goals and problem-solving together. And we're delighted to, again, welcome Dan here today.
So Dr. Chisholm is a mental health specialist in the Office of the Director at the Department of Mental Health and Substance Use at WHO. His work includes developing and monitoring mental health plans and policies, technical assistance to member states around health systems strengthening, cost and cost-effectiveness of strategies for reducing the global burden of mental health conditions.
Dr. Chisholm is a social scientist and health economist by training. He's worked extensively in academia and throughout the UN system and has published a number of seminal works including being part of the Lancet Series on Global Mental Health and the disease control priorities that are dedicated to mental, neurological, and substance use disorders. Again, we're delighted to have him. And I'm going to kick off the talk by first asking Leo to kick off the talk by walking us through some framing.
DR. LEONARDO CUBILLOS: Thank you, Collene.
DR. LAWHORN: Sure. I'm just going to--
DR. CUBILLOS: I'm so glad to have you here. I want to start with a personal story before I turn to the clinical side of things. I initially trained as a physician, but then I turned to the dark side of the force and I became a health economist. And I worked as a health economist for 15 years or so in different capacities. And then when I was in the World Bank, my heart started pumping real blood again. I was like, "I want to go back to medicine. And I want to go back to my truest dream of being a psychiatrist. But I don't want to lose health economics as a field where I can practice. But there is this-- mental health economics does not exist."
That was my thought. "Maybe that will not work out." But then someone mentioned, "Leo, have you read these articles of this guy called Dan Chisholm?" I'm like, "Who is Dan Chisholm?" So I went to PubMed and I did mental health economics and I-- of course, Dan's name appears there. And I found a plethora of his literature.
And I read it in and out, like, "Jesus, this is an incredibly exciting field, mental health economics." So in many ways, as I shared with you earlier, Dan, you have been very important in my career. And it's such a pleasure to have you here at NIMH giving us your thoughts and experiences about this field of mental health economics. At a personal as well as at a professional level, thank you so much.
I'm just going to have three slides to frame the talk of-- to frame why I think health economics is important as NIMH. So [three?] very basic 101, what do we mean by economics? We can mean so many different things. It is the study of how people make choices. It is the study of how people make decisions under scarce resources. It is the branch of science that studies behavior and decision-making.
But it can also be the science that studies how incentive structure changes decision-making and how people use values to frame decision-making. So it isn't all about people. It is about choices. It is about scarce resources. It is about budgets, but it is also about values. And all of these apply to societal problems with the initial goals of increasing efficiency and equity, so there is no single right definition of economics. And that's just like-- so some example of questions that we can try to answer or at least approximate an answer in health economics are these eight: what explains the rise in the opioid epidemic? How does health insurance affect household financial security? How does moral hazard affect total health costs? What are the drivers of rising drug prices? To what extent have new technologies driven healthcare costs? How do physician payment mechanisms affect physician behaviors? What drives or deters individuals to seek mental healthcare? And how purchasers or payers choose which new technologies or interventions to fund?
And I think that last question is very critical to us. In many ways, the science we do at NIMH, or at least the science we do in Global Mental Health, is about adapting or adopting or creating new interventions to a particular field; that we hope that those interventions be adopted by those health systems, and for them to be adopted and implemented, the people at the top, the people who are making decisions should decide to choose them and fund them.
So how do they make decisions? That's a critical question for us, and that's one of the areas where I think health economics is important for us. Next is the last slide that I'm pulling. This is a very old figure called the Plumbing of Health Economics. I'm referencing an article of 2000, but actually, I think it appeared sometime in 1993 or 1997. And you can see, from A to H, different areas where health economics can help us understand health systems.
Now we'll quickly go through A, what influences health other than healthcare? And this is what we call social determinants of health. What is health - I'm going to B - and what is its value? So this is where we talk about value of life, utility scaling, [inaudible], and so forth. When we go to C, what is the demand for healthcare? Those are questions about how and why do people choose to seek mental healthcare or choose to not seek mental healthcare. And this is very important when it comes to [inaudible] populations, patients, and people or persons with this experience. Going to D, supply of healthcare; what are those aspects that affect the production of healthcare professionals or the production and distribution of pharmaceuticals or the distribution and quality aspects of psychosocial interventions, for example?
Going to E, this is more of what? Cost-effectiveness and cost-benefit analysis - and many of you are very familiar with it - is the microeconomic evaluation at the treatment level. Should we decide to do CBT versus CPT, which one could be more cost-effective? And then going to F, G, and H, those are more at a macro level, particularly G when we evaluate the health system level efficiency and equity and where we see points where maybe in some populations are not adequately treated or may not be adequately accessing services maybe because there is not a enough availability of services.
So health economics things, all these things into perspective is not only about cost-effectiveness. It's not only about cost-benefit analysis. In my mind - and this is probably the single message that I think could help us understand and frame the value of Dan's talk - all this science we produce at GMH and potentially at NIMH at the global level will hardly be adopted by health systems around the world without utilizing the different techniques and skills in areas where health economics provides analysis. For us to move to [connotation?] science and for us to make sure that the basic explanation of science that we provide gets actually an access patients and changes treatments on the ground, health economics is an essential tool and an essential science.
So with all these considerations, I want to, again, welcome you, Dan, to NIMH, to our Global Mental Health team. Thank you for making the time to share with us your thoughts and knowledge and also thank you for your patience. This talk was initially scheduled in December, and for different reasons, we are [half posting?] it now in March. Over to you, Dan.
DR. DAN CHISHOLM: Thank you very much, Leo and Collene, for the very warm welcome. Great to be joining. Yes, third time lucky I think this is. I got COVID in January, and then I think one of your former directors was leaving at the time we had scheduled for December. So great to be eventually joining you and looking forward to the discussion.
So I will try and speak for maybe half an hour or something like that and leave some time for questions and discussion. I hope that accords with the time we have available. And just to send warm greetings from Dévora Kestel, the Director of Mental Health and Substance Use here in WHO headquarters where I'm actually sitting for once. We're slowly coming back to work, and so I'm actually in the building.
So let me kick off, and I think the introductory slides that Leo just showed provide a good starting point for thinking about-- first question is, well, what are the types of questions that we should be asking and could be addressing through analytical approach to mental health economics and financing? So I also have a sort of slightly different way of structuring some of those questions from a kind of global mental health perspective and from a public health perspective sitting here in WHO. So, Collene, if we can have the next slide, and this was asking about some of those basic questions about, yes, what questions should we be trying to address?
And I put that first, just because sometimes I get frustrated, certainly, when I see or read things and it could be very interesting, but you worry about the application to the real world. And there are so many real-world problems out there, always want to sort of focus on things which can really help to address those challenges and problems that are faced. And then of course I want to address what evidence is already out there and being used to inform policy and practice. But then finally, a more reflective question which could lead into some discussion about how can we better embed health economics and financing within policy planning and services research, particularly with respect to mental health.
So next slide, please. And I'll just start with this one, which is, again, a sort of starting point for much of how I've been trying to frame the question and how do we-- it's about investing in health, and that can be understood in different ways. And the investment case which we try to build up over many years of course can be predicated on non-economic, non-financial grounds in terms of the foregone health, happiness, and well-being that results from mental ill health as well as the foregone rights, opportunities, the inequalities, as well as foregone income, production, consumption opportunity.
So these are the kind of classic sort of economic welfare arguments about how can we enhance opportunities for consumption doing the things that people like to do and to live a full and flourishing life. But then when we come more specifically to the economic arguments which represent one, but only one, set of arguments for investing in mental health, we can look at some of the economic losses that are attributable to mental disorders or health conditions, the availability of different intervention - looking at their affordability and cost-effectiveness - as well as broader assessment of-- more like cost-benefit analysis looking at returns on investment, not just in terms of health but also productivity.
So we'll try and cover some of those. If we go into the next one please, Collene. Another kind of framework, which is used a lot obviously in WHO and global health, is this kind of framework where we look at the different functions of a health system and what are health systems for and what are they trying to produce and where are we going?
So if you look at this slide, you can see the pertinence, the kind of quite significant attention that is given to issues of health financing there in the middle about the revenue-raising, pooling, and purchasing functions and what that leads to in terms of relative improvements in efficiency but also equity, and ultimately, trying to resolve and improve health but also improve or reduce exposure to financial hardship. And that ultimately is a fundamental part of universal health coverage; not just about the quality and the service coverage but also the financial coverage or protection. So I think these are useful frameworks to kind of think about, well, where should the research be going? What are the kinds of questions that we can sort of try and respond to or address using these investment frameworks and health system frameworks, UHC frameworks?
So I've got four here, which, the first one's the sufficiency question. And then a lot of the work to date, I would say, has been around the efficiency question, the cost-effectiveness evidence, much less on the equity. And I still think this is a serious gap, and there's lot that could be done to improve our understanding both around financial protection and inequalities and then that bigger question around sustainability. So we'll go through a few of these in turn.
So if we can go to the next one, please. Let's start with the sufficiency question. Sorry. I'm out of sync. So this was done-- I was just speaking to-- sorry, Collene. So these are the four kinds of questions again to look at. So we can go to the next one, start with the sufficiency one. And this is just to, I guess, make the point that-- well, challenging question. Is it ever enough, mental health spending? And what these graphs, which are taken from WHO's Mental Health Atlas for 2020, are basically just showing that there is actually a pretty strong and clear relationship between the wealth of a country and the amount that they spend on health generally but also on mental health specifically.
What is dramatically clear from the left-hand one is that the vast majority of countries with low levels of GNI - so low- and middle-income countries in particular - you can see are virtually near zero. They're spending extremely absolute amounts of money on mental health services, and there's just a few rich, high-income countries who are spending substantive amounts of more than US$200 per capita per year on mental health, which would be a few of the-- maybe the US and Canada or a few other OECD countries.
So on the right-hand side, you have just the percentage. So the correlation is not quite as strong, but it's still pretty clear, and there are a few lower-income countries which are spending towards 3, 5 percent of current total health expenditure. But there's still an awful lot which are spending a really tiny fraction. What, 1% or even less of total health expenditures go to mental health.
So this is a basic issue that if there's just no money available, it doesn't matter how many policies or well-meaning objectives there are. It's just not going to be possible to make services available on anything like the scale that is needed. So it's a somber picture actually in the world in most low- and middle-income countries and a major challenge on how to pool for greater investment in services. And of course, one of the arguments is that-- as I said, it's a multiple argument about cost-effectiveness, about human rights arguments, about UHC and equitable access to services, and so on.
So we have to use all of the information at our disposal, and at times, I feel like we don't have all the information at our fingertips, and therefore, you can't make such a strong argument with policymakers. Next slide, please.
This is just showing from a recent systematic review of the cost of mental disorders. So I put it in the previous slide, is it ever enough? And this interesting set of graphics as well you can go to in that website there which looking at the costs, the estimates of total annual costs for countries or per case or per capita, both by productivity losses as well as healthcare costs if you can look at these different distributions. But they're just showing this sort of basic gradient that if you think of it from a cost per case-- and there's an order of magnitude difference between the cost per case for some of these conditions. Index case would be schizophrenia versus, for example, anxiety disorder.
It's a tenfold difference in the cost per case. Now, the cost for a whole country wouldn't necessarily be of that type because of course disorders like depression and anxiety are far more common, and therefore, you multiply the cost per person to get up to estimates of the national costs, and often those are greater than the costs for more severe but less common disorders. Next one, please.
If you zoom in on some of those-- so for example, if we look at depression and anxiety, some research that I was involved in a few years back was-- it was really a return on investment analysis, but whilst we were about it, we did some calculations of the estimated lost days of production based on analysis of the available world mental health survey data. And it came up with an estimate, globally, of around 12 billion days or 50 million years of lost productivity.
And if you look at the economic implications of that, it's around $1 trillion per year, so vast amounts. And of course, on the right-hand side, people have days out of work for many reasons. And what the graph on the right shows for both the lower-income and the higher-income countries is both the kind of, if you like, the comparative loss. So I mean, basically, the bit on the top is showing the additional costs that are associated with these conditions. In other words, the number of days lost for conditions like depression and anxiety are higher than other conditions. So you can therefore see what the excess loss is over and above what is commonly incurred for health conditions generally. Next one, please.
And we'll go to the efficiency question next, and so let's keep going. Yeah. So this is a helpful article written by one of my former mentors, Martin Knapp, based at London School of Economics, and along with Ms. Gloria Wong. They prepared a nice overview of the current situation and did a kind of narrative review of the cost-effectiveness evidence base, and basically, where are we? And we have a lot more data than we did before but still quite variable when you look across these different areas.
So we know that, for example, for depression and other common mental disorders, there's an increasingly substantial evidence base upon which we can make stronger and more confident claims of cost-effectiveness. So SR, Systematic Review. 22 Systematic Review, so depression and other common mental disorders. Also for psychosis and severe mental illnesses a fairly substantial database and evidence base now, whether for adjuvant CBT alongside anti-psychotic medication for psychosis and for early interventions. But for other areas-- so for maternal mental health, for example, child and adolescent mental health, we have far less studies. So this is indicating where some of the main gaps currently exist. So worth a look if you want to get a up-to-date sort of overview of where the evidence base is now. Next slide please, Collene.
So that review was mainly reflecting the evidence in higher-income countries, published research. And what about the low- and middle-income countries? And here we have far less trials. There's less money. There's less research. There's less publication, so there's less knowledge about the costs and cost-effectiveness. So we're forced into a different kind of approach, really, which is to use the data that we can take from systematic reviews and those few studies that have been done and do some extrapolation, basically some modeling.
And this is what we did in this big volume called Disease Control Priority. There was a volume on mental health published about five years ago. And these were some of the interventions that we feel there is sufficient data or available data for. So these were by these different delivery platforms, so a mixture of policy and legislative measures for alcohol demand reduction as well as suicide prevention through pesticide bans, for example, some community or school-based interventions. But really, most of the work that was being done in intervention analysis is clinical interventions for common mental disorders, more severe disorders, as well as some neurological conditions like migraine and epilepsy. So I'll say a little more about these. Next slide please, Collene.
So this has been collated, the evidence that we have built up and modeled for low- and middle-income country settings now appears as a menu of cost-effectiveness interventions for mental health, which was approved a couple of years ago. And this is using a methodology that was developed 20 years ago with Chris Murray and colleagues back in the day around the year 2000, which is, I think, when I joined WHO, to essentially look across the whole range of public health areas and interventions and carry out sort of comparative, so-called generalized cost-effectiveness analysis in order to identify where efficiencies could be identified.
So a lot of work went into this, not just in mental health but in most other areas as well, and we've accumulated that database. So it comes out in funny kind of ways. Let's go to the next slide.
So highly abstract. So you can see at the top that the results here have been at extremely aggregate level - and this is what our WHO member states wanted to see - not contextualized to a country level. So that's a separate part of the job is to do that adaptation and local analysis. But this is like regional and global analysis which just even though it's very abstract and aggregated, it's still just using really, again, order of magnitude differences. You can begin to see alarming or substantial differences in the cost, the effectiveness, and therefore the cost-effectiveness of different intervention strategies.
So here we've got some population or community-based ones. Socio-emotional learning in schools, for example, with a cost per capita of less than 10 cents compared to interventions for psychosis in upper-middle-income countries which would be maybe up to around 3 or 4 or 5 dollars per capita of population. And again, some of the interventions are really not that effective at a population level. Indicated socio-emotional learning programs, less than 10 healthy life years gained per one million population. Not a massive amount, whereas you have other interventions which will have 10 or 100 times more effectiveness. And that translates of course into wildly different cost-effectiveness ratios. So this is the purpose. It's like the kind of high level of priority setting and identifying what are the better buys and the less good buys in health sector decision-making.
The next slide, please, which just is another example showing the analysis for alcohol interventions. These are the population-based ones as well as looking at counseling for alcohol. So same sort of methodology. So maybe we'll just go on interest of time. So the next question is, okay, we've identified some cost-effective interventions. But then, that doesn't necessarily mean they're still affordable.
So I'll give an example. I mean, one of the policies and a good cost-effective intervention for cardiovascular disease would be to basically implement a - what do you call it? I just lost the word - a very comprehensive screening program so that you identify people at-risk at a relatively early age. But it is very cost-effective because it produces enormous amounts of health gain but is actually very expensive as well to do, and it wouldn't necessarily be possible to adopt such approach where health budgets are very limited. So the question of cost of scaling up is a different one to the cost-effectiveness. And this is just showing again from this Disease Control Priorities project some of the implied costs in different parts of the world at different levels of income and what even a really basic package like the one shown here could or would cost. And it's ranging from 1 or 2 dollars in lower-income parts of the world to 3 or 4 in low- and middle-income countries and up from there.
So maybe we go to the next one, because I think this also is an interesting one to look at. So over and above the actual costs of scaling up, can we also consider what are the non-health benefits? And so this analysis is an unusual and something called extended cost-effectiveness looks at the effects or the benefits of moving towards more public finance of interventions and what would be the value of that in terms of reducing inequalities with respect to access and financial protection.
And so this analysis, for example, for psychosis, depression, and epilepsy in India, we're able to look at both the averted out-of-pocket spending associated with moving towards a universal health public finance model and also the value of insurance to different quintiles of the population, and showing clearly that there is most of the extra value of financial risk protection is bestowed on people in the lower-income quintiles. Okay. So I'll rattle on, and you can ask questions at the end. You may have some in the chat, but I can't see that right now. So we'll come back to that at the end.
Okay. Let's go to the next slide, please, and just to cap this section off. So this is the kind of end-- this is what we were missing until quite recently. We had quite a lot of estimation of costs and cost-effectiveness, but we weren't capturing some of those other non-health benefits of intervention. So we developed some guidance and an analysis quantifying not just the health benefits but also the productivity gains that could accompany scaled-up access and treatment.
So we did this global analysis, which I'll show in the next slide, but just to say that there's been quite a lot of appetite in these-- there's some examples here from countries to carry out this kind of analysis at a national level to inform their policy and their planning and their benefit package specification and so on, which is, I think, encouraging and a good way of engaging not just health but other ministries and partners in the discussions.
So the next slide please, Collene, has the bottom line results from this analysis which was carried out really for the World Bank and WHO side meeting of the three meetings in 2016, the Out of the Shadows meeting that was held then. And this was one of the analyses that was carried out to kind of support that whole meeting and basically show that by scaling up treatment for depression and anxiety disorders in general healthcare settings, you could get a fairly healthy return on your investment. So for every $1 invested, you're getting between 4 and 5 dollars back in terms of restored health and productivity.
So it's an important argument we're able to make in advocacy, and it's not perhaps comparable to some areas where it might be 15 or 20 or 30, but anything more than 1 it means it's worth doing, right? So it's been helpful and influential, this analysis. Okay, let's move to the equity question next. How are we doing for time? Are we all right? Another 10 minutes or so?
DR. LAWHORN: Yeah, I think that would work.
DR. CHISHOLM: Okay. So for the equity question-- I'll take it maybe with the sustainability one as well, the last two questions we shall cover. So this is asking about the extent to which households that have a member with a mental health condition, how much are they really protected from the financial risks that are associated with that, and what is the access to care? So this brings us to the hot topic of financial fairness and out-of-pocket spending on health.
So the next slide has a bewildering array of numbers and figures. But the one on the left, the big box there, just showing the composition of health spending in different regions of income strata. So you can see that in low-income and low- and middle-income countries, out-of-pocket spending, direct spending by households is accounting for more than 40% of the total spending, whereas in high-income countries, it's more like half that, 20%. And really, this is hugely problematic because, of course, out-of-pocket spending is regressive.
So the people who are at those lower ends of the income spectrum end up paying proportionally more for health services that they need. And if they're really poor, they don't even seek health services because they can't afford them. So some of these numbers at a global level are here on the right. You can see, for example, that up to one billion people in the world are spending more than 10% of their household budget, and if you take that threshold up to 25%, which is really extreme and a pretty high amount, it's still 290 million. And those numbers are rising as you can see.
So this is just being made even worse, of course, by the COVID pandemic, and there's been lots of reports or calls on the impoverishing effects of the pandemic including on health spending. And some of that is captured a bit below. You can see that, again, by country income group, for example, the lower-middle income countries, financial reasons still are substantial. We can see the impact of COVID on their ability to access the healthcare services is due to disruptions to services. But in low-income countries, you can see that it's still by far the-- that it's the financial cost which is the main barrier to accessing services and care that they need.
So with that in mind, the general context and stats, I just want to spend a minute or two - if we go to the next one please, Collene - on something we call the EMERALD project, standing for emerging mental health systems in low- and middle-income countries. So this was an EU-funded project actually and looked at some of these questions down below including on adequate, fair, and sustainable resourcing for mental health.
So we did this in six low- and middle-income countries, four in Sub-Saharan Africa as well as India and Nepal. And I just want to draw on this because it's one of the relatively few recent studies that has looked into this whole question of the out-pocket spending. And we were able actually to undertake a household survey and look at these household economic burdens associated with mental health conditions, so. Go to the next slide, please. So as part of an overall framework for thinking about sustainable mental health financing, which would be the kind of bottom-right part of this, there are various elements that you would sort of need to have, data points.
And of course, you need to know something about the local disease burden and the health system and also importantly the macro-fiscal situation because that will of course determine amounts or level of spending by government on health and how much can be borrowed and so on. But part of it often lacking is information about the extent of unfair financing effectively in the population, so this is what a household survey can help to respond to. So we can go to the next slide.
We basically ask a number of questions about what is the extent of the risk protection and what is the value of providing great protection. And of course, across these countries, we found really quite pronounced effects that of course are not protected. And if we go to the next slide, this gives some nice examples of what I was talking about.
So for example, 16% of households with a member having a mental health condition reported withdrawing their children from school compared to around 9.9% - so another 50% extra compared to households affected by other chronic conditions - 31% reporting reducing their use of healthcare versus 20%, and 36% reducing their frequency of meals due to financial hardship compared to 26%. So you can see consistently there's a kind of 50% or 1.5 times higher implication of this compared to other chronic conditions. And if we go to the next slide, this sums up some of these points, I think, that households and individuals who are exposed to adversity, whether unemployment, indebtedness, inadequate access to basic amenities, housing, education opportunities, and so on, of course we know have a link and increase the risk for mental illness, and inversely, the experience of mental illness or ill health for individuals and families only exacerbates the level of socio-economic adversity and will increase their risk of impoverishment.
So as I said earlier, I think this is really a still relatively unexplored area and could be important to address through further research because, as it says on the right, the more evidence we have, the more we can sort of make clear arguments for inclusion of mental health conditions in universal health coverage plans and efforts as well as helping to argue for greater investment in influencing the upstream determinants of mental health.
Okay. So we're nearly there. I think just a couple of concluding slides. The first one is just some kind of like a checklist of things which could be considered by countries when thinking through how to move towards fairer and more sustainable financing for mental health. And as I said, we've developed this framework, and you can sort of follow that through and look at some of these-- look at the existing service for funding gaps, find out who's really paying now - is it households? Is it governments? If so, what are they contributing to those costs? - and through that reveal perhaps existing inequities. And then following that, then exploring different financing options. One of the clear standout recommendations for low is as countries are moving towards UHC, then it's vitally important to include mental health in those efforts or in those schemes or benefit packages.
So I think those are the main points. And I think my last slide is the next one, just some research questions that I think come out from what I've been saying for low- and middle-income countries. So one is actually basic: how much has been spent on mental health service? It's actually quite a hard question because the boundaries are quite porous and the awfully big data availability problems, so.
But if we don't know that, then we're already on the back foot. As I was saying, knowing more about how much households are incurring and paying for as a result of a household member having a mental health condition, and then of course the prioritization agenda, so [which?] interventions in a local context represent good value for money but also address these existing inequalities in the population, and of course the costs and the resource implications of integrating services as well as scaling them up, and identifying synergies with, for example, NCDs or other major disease program areas in countries so that we're avoiding a siloed vertical approach to planning and practice.
It is improving. [There's been?] some recent systematic reviews looking at the economic outcomes and benefits of better mental health. And I know that Michael and [others?] have looked into this in the past and reported and [Yogen?], [inaudible], and colleagues. But looking at some of those broader non-health benefits of intervention and treatment as well as looking at actions on addressing the social determinants of mental health as well and also the structural determinants of mental health. And then the final one is around the more health financing question around how to extend financial protection and service coverage and making the move towards UHC.
So I think I'll leave it there. And thank you very much for your attention and your time, and happy to take any questions and have a discussion on any of these topics that you wish, or if you want to ask about other things as well. What's going on in Ukraine? I can also provide some points on that.
DR. CUBILLOS: Thank you so much for your presentation. I was responsibly taking notes here. May I kindly ask you to explain to us what UHC means? You mention it multiple times throughout your presentation, and I wonder whether it would be important to elaborate what those three letters mean and the concept behind them.
DR. CHISHOLM: Okay. Yeah. Maybe I should have used the-- there's a well-known box which describes the so-called three dimensions of universal health coverage, which I think the key provocation was the World Health Report in 2010. And essentially, the three dimensions are to do with the breadth which has to do with essentially the access to services; the second one is the depth which is the kind of range of services, so what is the mix of the interventions that people would have access to; and then there is this important vertical dimension which is the extent to which people are expected to pay out-of-pocket or contribute to the cost of care.
But in essence, the definition of universal health coverage is that people should be able to access the services that they need without undue financial hardship. So they shouldn't be disqualified from getting care because they don't have enough money in their pockets. So that's why financial protection insurance is so vitally important because it provides for when people need services and doesn't discriminate according to people's ability to pay for those services.
So it's an equalizing policy which, of course, requires contributions, but the contributions-- taxed-based insurance is progressive. So the more wealth you have-- more money you have in your pocket, you put a percentage in, so that's more money going into the scheme than people who've got very low incomes. And there are exemptions for people with no incomes or very, very low incomes. So I think that's the concept in a nutshell.
DR. CUBILLOS: So it is a way to think about allocating public funding to health services to alleviate financial hardship, in this case in mental health.
DR. CHISHOLM: Yeah. And it's beyond that. I mean, the Director General of WHO, he talks about universal health coverage being the kind of unifying goal in health because, if you think about it, it brings together so much because it's not just limited to the care but also the prevention and promotion aspects of services. It brings together both the access and the coverage at the service level but also this financial coverage or element which is, of course, a vital objective of health systems is to have fairness in financial contributions to the services.
DR. CUBILLOS: Thank you, Dan. I would like to invite people to raise their hands if they have questions.
DR. LAWHORN: And also I want to acknowledge that I know a bunch of people have to drop off at noon. So if there's anyone who has a pressing question who is playing with their noon drop-off time, maybe you could go first. And then I'll let Leo moderate.
DR. ANNA E. ORDOÑEZ: So I'm one of those people who needs to drop off at noon, Dan, so I will-- we've seen in a lot of the-- at least in the global mental health studies that study teams are trying to include cost-effectiveness analyses in their interventions and struggling with-- I mean, I think it's a whole area of expertise that just measuring some of the data, the cost is difficult to begin with. But I'm just wondering if you have thoughts - you're pointing to data and sparsity of data in lots of places - if you have thoughts of how to better contribute to the data through the research that's being conducted on mental health interventions. Are there things that we could do more systematically to help contribute to thinking through cost and benefits of all of these different interventions that are being tried? And you're on mute [laughter].
DR. CHISHOLM: Thank you. It's a very good question, and one confronted quite a bit in the past. At one point, the Grand Challenges Canada, your partner in Canada, they were funding 60, 70 projects around the world on global mental health, and they were pushing for this kind of poll metrics and trying to include these. And it is a struggle because it's new. It's new techniques. It's like, "Oh, whoa." People sort of glaze over, or it's like rabbit in front of the headlights when you start talking about costs and economics and things like that. So I just try and literally demystify it by saying, "Look, you're really good at measuring outcomes, right?" because these are researchers, right? "You're really good at measuring outcomes or social functioning or symptoms or whatever. So why can't you just add-- why can't you just measure also at the same time some questions about, 'Well, what happened to those people in terms of their employment or some of these other outcomes?' but also ask them, 'Well, what services did you receive?'" Because those are the basic questions.
And then of course you need someone in that team or an external consultant or someone to maybe help do run some of the numbers and turn those basic questions into a set of costs and then do some cost-effectiveness calculations. And there's different levels. It can be extremely sophisticated, but some of the trials including the NIMH global hubs which had that component, they were quite, I would say, rudimentary, but they still were capturing those key dimensions of cost and cost-effectiveness. So it can be done, and we were doing it-- I mean, the GCC had a opportunity. And obviously, you still probably have annual meetings, COVID aside, but where you have gatherings and you have workshops and opportunities for people to come and listen and learn a bit and build a bit of confidence, really. So I think those are the key things.
DR. CUBILLOS: Before I pass it through Sarah, Dan, Anna who just asked the question is our director for the Office of Clinical Research, and this serves as a way to ask people to introduce themselves, given that Dan doesn't know you. Name and perhaps affiliation or [IC?] in the case of Sarah. Sarah, go ahead.
DR. SARAH DUFFY: Thanks a lot. And I'm Sarah Duffy. I'm from NIDA, and I'm the economist at NIDA. And I actually have a different question. It's more about policy and how you explain all this to policymakers.
The underlying assumptions of the universal healthcare, the UHC-- I don't think it'll be surprising to say that we probably, in this country, have some political opposition to some of that. But I'm just curious, particularly when trying to extend this to lower- and middle-income countries, is there that same kind of maybe political opposition to that kind of thing, or do they kind of say, "No, this is something we think government should be doing"?
DR. CHISHOLM: Very interesting, yeah. Look, it's partly about the social models that are predominant and principles around liberty and so on. I mean, from a public health perspective, and I guess that's where I'm-- when we're going and talking to ministries of health, there may be some confusion about how to run these numbers or understand them.
Many people have no idea what a disability-adjusted life year or a quality-adjusted-- it's like, "Well, what does that mean?" They don't really know. Why should they? But they get the value for money point. I mean, they are working with limited budgets, and that's why more and more requests are coming in and demanding of WHO to advise them about, "Well, where should we be putting our money?" What are the best buys, basically? Very simple. And so we spend all this time cranking through these numbers and then we present them back and say, "Well, look, this kind of quite high-level, regional-level analyses suggest that you should be doing X, Y, and Z, but you should be reconsidering doing A, B, and C because you would do much better, get much more health gain by doing X, Y, and Z."
So then that moves into a conversation of how you transition from less optimal to more optimal allocation of resources which can be painful and political and everything else. But I wouldn't say there's much opposition to the concept of securing better value for money. But I appreciate that in some other places, including our own country, that can be seen as an affront, and the dreaded word rationing comes up, and it's like, "No, no rationing here." But that's--
DR. DUFFY: Exactly. Or even the idea that people should have healthcare, but. In any event, I digress. Thank you so much.
DR. CUBILLOS: Thank you. Sarah. James?
DR. JAMES ALARO: Hi. I'm James Alaro from NCI, National Cancer Institute. Thanks, Dan, for a great presentation, and thanks, Collene and colleagues, for organizing this.
So I guess from an LMIC perspective-- so I'm originally from Kenya where we didn't have a budget, let alone a health budget, right? And I remember growing up when mental cases-- first of all, they didn't go anywhere, right? They were not dealt with in any ways, [inaudible] ignored. Maybe things are changing now than they were.
What I'm wondering about is how you are able to compute the numbers that you have, assigning certain kind of numbers to what people are spending on health and particularly on mental. And I worry that depending on how you get there and how accurate that data is, we end up getting numbers and using those numbers to make policies while the numbers themselves might not be as rooted in the reality in this setting. So I don't know. Maybe you guys have better-- measurements have improved better than I last remember them.
DR. CHISHOLM: Thanks for the question. I mean, Kenya is a good example that there has been quite dramatic change and levels of interest gradually increasing over, I would say, the last 10, 15 years. And I mean, most-- I was showing you these investment cases. So one of those is in Kenya.
There is enormous interest from senior government and they actually have quite good data. So we're able to contextualize, adapt these kind of models and approaches that we have using local data and local expertise, of course, to inform about what is current levels of treatment coverage for different conditions. We can work out the cost to provide those services. Where we run in most into problems is the having local information on the impact of intervention.
So we're normally forced to retreat back to international estimates from systematic reviews. And that's a source of criticism because, as I was saying, most of those reviews are reflecting the evidence that is collected in higher-income countries. And so for some interventions, the effect size, they shouldn't really change. But the more culturally attenuated those interventions, the more psychosocial, the more psychological even interventions, the more questions are about, well, it might work in North America; it doesn't mean it's going to work in Kenya.
So that's why it's very important to build up and that evidence base has been building up in the last 10 years, including with NIH support; increasing evidence of what works in these low-and middle-income country settings. So that's really, really important, and it means that those kind of modeling studies that we do are more grounded in the local data. Yeah.
DR. CUBILLOS: Thanks, Dan. Mike?
DR. MIKE FREED: Hi. Thanks so much for a great talk, Dan. I'm Mike Freed. I'm the chief of the services research and clinical epidemiology branch here in IMH, and I'm a psychologist by training but a health economist enthusiast.
So I'd like to-- my question's kind of [based?] off of what Sarah asked, and I was curious if you could say a little bit more about, what do you find to be the most compelling arguments or strategies that would cause either a country or a health system or commercial plan or even local organizations to redistribute funds from low-value services to high-value services? And I ask this because a lot of what you talked about was cost-effectiveness analysis, and really cost-effectiveness analysis asks how much bank can you get for the buck, but you really need to have the bucks to put somewhere.
DR. CHISHOLM: Well, couple of points I can say. The arguments that work best vary from place to place. I think it's really important to have a set of cards in your hands. This is what happens in reality. In my virtual bag, when I go traveling and other colleagues [we're meeting?]-- so in some contexts, human rights might be a very powerful, strong argument. But in other countries, which we won't name, human rights wouldn't be an effective argument. It's not going to shift the current-- whereas talk of economic efficiency or burden-- sometimes you see economic burden can be very significant.
I know that the investment cases on non-communicable diseases and also mental health in Uzbekistan, for example, that I was involved in, it opened up new doors, and it was the numbers showing the impact of mental health conditions and NCDs on the economy when you're taking to account those broader losses in productivity. That's what got the interest. So that's the first point is the arguments are many and varied. It can be around social inclusion. It can be around human rights, but it could also be around economic or economic efficiency, so.
And then the transition. I mean, I think one of the key ones, of course, in mental health that we've been pushing for so many decades is trying to move away from a reliance on institutional psychiatric hospitals and other long-term institutions as the basis for mental health services because these are often not good quality. They're remote. They're not improving the outcomes. People stay there for life. So we're pushing hard for a transition towards community-based services, and there's a lot of buying with that as a concept, as an idea, as an approach.
But it's still really hard to do in practice because we know from the experience of high-income countries that it's a long and expensive process. And low-income countries can have all the intent, but they don't actually have the dollars to make that big transition and build up community mental health services before you start closing these big psychiatric asylums. And we have some horrible experiences with countries including South Africa and more recently Ukraine about three years ago where they changed this sort of policy and there was terrible consequences for people that there were no places for them to go and there were a lot of avoidable debts that happened as a result of that overly swift change in policy and trying to transition too quickly.
DR. CUBILLOS: Thanks.
Thank you, Dan. I'm going to read-- before I give the floor to Andrea, I'm going to read a question from Unja Hayes. Unja works at another National Institute of Health institute called the [inaudible] International Center. So her question is then, thank you for the great talk. One question that came through my mind during your talk is about service provision. What is the state of health professionals trained/available to provide mental healthcare in low- and middle-income countries? And thank you for discussing inequities with economically and socially marginalized groups within a population. Their need for services is likely more-- the access is likely [inaudible]. So again, her question is, what is the state of health professionals trained and available to provide mental healthcare in low- and middle-income countries?
DR. CHISHOLM: Yeah. Crucial question because of course human resources are the backbone of any health service. And bottom line is, a bit like the money I was showing at the beginning, there aren't nearly enough trained mental health workers. So by that I mean a combination of specialists like psychiatrists or psychiatric nurses, psychologists, but also non-specialist. So that would be the general hospitals and the primary healthcare practice, and then there's maybe a third level which is more community-level workers who could be lady health visitors who go or are walking out in the community. So those three levels, and there's basically a lack in most parts of the world. Certainly Sub-Saharan Africa, Asia-- insufficient numbers for sure.
And then the question's what to do about that. And most of the focus that we certainly make is on the non-specialist. So we have programs. One's called mhGap that's about building up the capacity of non-specialist primary health providers. Could be nurses, social workers, as well as primary care doctors in the identification and management of priority mental, neurological, and substance use conditions. And that package, for example, is being used in more than 100 countries worldwide and is very well accepted. I don't know. We're still using, if you like, quite old fashion teaching techniques. And there's only so many people you can teach, and it takes five days to do that course. So I think there's opportunities for improving access to some of these tools through digital and other means, but. So that's about the quantum.
And the other key topic, I think, in this is around competency. So who needs to be able to do what, in what place, with what responsibility? So a lot of countries, nurses are not allowed to prescribe. Well, that's just an old-fashioned thing maybe, and they just didn't update the legislation or the regulations. There's no reason. And we know that community-level providers, even peer workers or lay workers, can actually provide psychosocial interventions. Don't need a psychologist.
So it's about matching the needs at different levels to the functions and the competencies, and. So having a sort of competency-based approach to developing the mental health workforce is really important. Because otherwise, you can be stuck with rather old-fashioned ideas then it never changes, and it's a very biomedical, hierarchical kind of approach to human resources.
DR. CUBILLOS: Thank you, Dan. We have probably five to seven minutes left. Andrea?
DR. ANDREA HORVATH MARQUES: Hi, Dan. Thank you so much. So I work at the National Institute of Mental Health research. And just quickly I just want to thank you. And you mentioned about how it's important the recent unexplored points like looking for the social determinants of health impact on mental health. And that's something that [inaudible] pushed few years ago. And I wonder, in that sense, how can [Grand Challenges?] [inaudible] and other agencies connect with WHO in a sense of-- how is your partnership being more effected to move things forward?
DR. CHISHOLM: So is it about the research agenda, or?
DR. HORVATH MARQUES: Yeah. I think our research agenda and how it kind of aligns with a lot of things that WHO goals are. So how you think an effective partnership could be supported to move some agendas forward?
DR. CHISHOLM: Well, I think meetings like this are good that there's an exchange of ideas and also understanding. Hopefully, one of the benefits of this kind of interaction is that you get a better sense of where we're coming from. What are the priorities of WHO? What are we trying to do? What's our program of work? And what are the kind of key concepts and topics and issues?
So then what are the research needs that accompany that? So that's one way. But the other way is us better understanding what are the priorities of your institutions and looking for those synergies and see where there is a good match. And then off we go. And then there are different mechanisms for which that can be done.
And WHO, of course, is being involved in many of these research projects and programs. For many years, there was a collaborative agreement which enabled us to develop some new instruments and tools and ICD. And then there was the WHODAS and things like that I remember from many years ago. And then it's continued.
I mean, the collaboration between GCC and NIH, they were talking closely so they would not overlap, not duplicating, and. So best regards to Beverly. I used to enjoy my interactions with Beverly. This is the way to go. So I don't know if I really answered your question well. But I mean, totally open for more constellations and collaboration, particularly on sort of low-middle-income countries. And the types of research, it's kind of-- yes, of course, there's the clinical trials, and we've benefitted enormously from a big increase in funding for that. But where I see, perhaps, still big needs and gaps is more the health systems, health policy, health implementation research, which gets in a bit messy and muddy. But actually, it's quite important to be able better understand some of the processes that enable and allow for these interventions which are effective to actually be embedded and be successfully scaled up in countries.
DR. CUBILLOS: Thank you, Dan. Collene?
DR. LAWHORN: So I hope I can get this in and still be able to give him the last minute. And I'll try to be quick. And this is for Dan and maybe for Leo as well. And so this idea about cost-effectiveness and feasibility is really interesting in terms of when we think about capacity building and what we want for the next generation or training in the next generation of future mental health researchers and mental health economists.
And I struggle sometimes with the idea that our capacity building is often around, in LMIC settings, a reactive space that's based around what the greatest need is. And I get that, but how do we also build a space for pure scientific innovation and to encourage all junior or thriving scientists to be able to take risks and for us to invest in those risks even if it may not be as cost-effective from a feasibility standpoint given that it's a new space they're venturing into? I wonder if either of you have thoughts on that balance, or. I don't know.
DR. CHISHOLM: I mean, of course. You want to encourage, stimulate innovation and give young, bright minds opportunities to get their fingers and hands into projects which are supported. So I think it's partly just the mechanisms, right? I mean, there are different opportunities and mechanisms to stimulate young researchers, right, who maybe have never had a grant before but there is seed funding to give them the opportunities to present and then be supported with their ideas. It doesn't mean giving a million or 5 million. So I think there are different mechanisms that can be-- yeah. I'll let Leo go to see if I can think of any other useful thoughts to contribute.
DR. CUBILLOS: I guess it also involves having a different risk profile to some extent; being willing to be more risk taker than the average. And it's about innovation. Innovation is riskier, but it's worth it. [inaudible]. This is worth [adapting?].
DR. CHISHOLM: Yeah. I know the dilemma you're referring to, Collene, because if it's too many restrictions or too many kind of expectations like, "Okay, we're just interested in building up clinical trial evidence," then that actually effectively eliminates a lot of people, right, from developing or testing their ideas for innovation. Yeah. But I've seen, just in the latest call, there are calls targeted at low- and middle-income countries and it's on implementation research and health systems. And that's very refreshing to see.
DR. LAWHORN: Great.
DR. PIM BROUWERS: Thanks, Dan. Very interesting talk. So I'm the Deputy Director of the Division of AIDS Research. My question comes a little bit out of my background on HIV.
So the reason we got an enormous amount of funding and spending on HIV was through activism we had act up and other groups. And so that was the one part that I missed a little bit in your talk. It looked like a lot of the activities were all top-down rather than from bottom-up.
And so I was wondering whether in your evaluations around the world of-- to what extent your mental health components were included in policies because the politicians react to the public demands, whether you also looked at activism in those countries, and to what extent that actually had a significant impact on whether or not it was more mental health funding. And then basically for Leo and Andrea and other people in global mental health and particularly for Collene who's particularly interested in communication, is there a role for NIMH to try to see whether we can actually boost that kind of activism?
DR. CHISHOLM: Yeah. Great question. Thanks a lot, and this may be a good place to end as well. So I mean, it's easy to say at a policy level, user engagement and empowerment is a fundamental principle of WHO's action plans and policies and programs in mental health. And we see progress.
I mean, a lot of countries still it's a huge challenge and you don't see meaningful or real engagement of service users or their representatives in planning and policy and evaluation. But we know from experience and previous studies that of course the inclusion of such people makes a very valuable input into those policies and plan and also research. This EMERALD project I was talking about, there was a distinct strand of that which was devoted to exactly looking at the engagement and impact of service user perspective on the research agenda and process that was followed. Really interesting.
If I didn't cover that it's because I think really when we're talking about sort of analysis of cost and effectiveness, it is rather than a kind of high level somewhat top-down sort of exercise where you're trying to look à la carte for technical efficiency. But when we start coming to what I was saying is needed which is more the kind of implementation research, that's why it's absolutely critical to have local service user engagement but also other local actors where services are going to be implemented and rolled out. Community leaders, whether it's teachers or religious leaders, they're tremendously powerful or important in these local contexts, and so they're very much part of the engagement and the stage of that kind of implementation.
DR. LAWHORN: Well, thank you, Dan, so much, and thanks to everyone who is still with us. Sorry this went a couple of minutes over, but much appreciation to you, Dan, for this very illuminating talk, and we hope we'll be able to continue to work with you. And much thanks to Leo for framing this talk and helping to really bring it into NIH and NIMH in ways that we can continue to think about and thoughtfully engage. Syed will be sharing the talk or slides and everything else, right?
MR. SYED RIZVI: Yeah, I'll put the link in the next digest.
DR. LAWHORN: Okay, great. Thanks so much to everyone. Enjoy the rest of your day or night.
DR. CHISHOLM: Yeah. Thank you very much. Been great fun, and look forward to continued conversations. Have a good rest of the day, guys.
DR. CUBILLOS: Looking forward to that too. Dan. Thank you.
DR. CHISHOLM: All right. Thanks a lot, Leo. Bye.
DR. LAWHORN: Bye.